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Phonetic convergence in interaction ; Convergence phonétique en interaction Phonetic convergence in interaction
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In: https://tel.archives-ouvertes.fr/tel-00822871 ; Autre. Université de Grenoble, 2012. Français. ⟨NNT : 2012GRENT079⟩ (2012)
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Bayesian Speaker Adaptation Based on a New Hierarchical Probabilistic Model
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In: Electrical and Computer Engineering Faculty Research and Publications (2012)
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Using articulatory adjustment to compensate for hypernasality - a modeling study based on measures of electromagnetic articulography (EMA)
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Speaker similarity evaluation of foreign-accented speech synthesis using HMM-based speaker adaptation
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In: http://www.cstr.inf.ed.ac.uk/downloads/publications/2011/wester_icassp_2011.pdf (2011)
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25 |
Computational differences between whispered and non-whispered speech
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Speaker similarity evaluation of foreign-accented speech synthesis using HMM-based speaker adaptation
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Unsupervised intralingual and cross-lingual speaker adaptation for HMM-based speech synthesis using two-pass decision tree construction
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Gibson, Matthew; Byrne, William. - : IEEE Transactions on Audio, Speech and Language Processing, 2010. : IEEE Transactions on Audio, Speech, and Language Processing, 2010
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30 |
Thousands of Voices for HMM-Based Speech Synthesis-Analysis and Application of TTS Systems Built on Various ASR Corpora
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Thousands of Voices for HMM-Based Speech Synthesis-Analysis and Application of TTS Systems Built on Various ASR Corpora
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Speaker adaptation and the evaluation of speaker similarity in the EMIME speech-to-speech translation project
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Two-pass decision tree construction for unsupervised adaptation of HMM-based synthesis models
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Cross-lingual speaker adaptation for HMM-based speech synthesis
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In: http://isca-speech.org/archive_open/archive_papers/iscslp2008/009.pdf (2008)
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Cross-Lingual Speaker Adaptation for HMM-Based Speech Synthesis
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36 |
Speaker Adaptation of Language Models for Automatic Dialog Act Segmentation of Meetings
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In: DTIC (2007)
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37 |
Nonparallel Training for Voice Conversion Based on a Parameter Adaptation Approach
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In: Departmental Papers (ESE) (2006)
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Non-Parallel Training for Voice Conversion by Maximum Likelihood Constrained Adaptation
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In: Departmental Papers (ESE) (2004)
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Abstract:
The objective of voice conversion methods is to modify the speech characteristics of a particular speaker in such manner, as to sound like speech by a different target speaker. Current voice conversion algorithms are based on deriving a conversion function by estimating its parameters through a corpus that contains the same utterances spoken by both speakers. Such a corpus, usually referred to as a parallel corpus, has the disadvantage that many times it is difficult or even impossible to collect. Here, we propose a voice conversion method that does not require a parallel corpus for training, i.e. the spoken utterances by the two speakers need not be the same, by employing speaker adaptation techniques to adapt to a particular pair of source and target speakers, the derived conversion parameters from a different pair of speakers. We show that adaptation reduces the error obtained when simply applying the conversion parameters of one pair of speakers to another by a factor that can reach 30% in many cases, and with performance comparable with the ideal case when a parallel corpus is available.
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Keyword:
gaussian mixture model; speaker adaptation; text-to-speech synthesis; voice conversion
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URL: https://repository.upenn.edu/ese_papers/45 https://repository.upenn.edu/cgi/viewcontent.cgi?article=1048&context=ese_papers
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Speech Recognition Using Dynamical Model of Speech Production Ken-ichi Iso \Lambda
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In: http://reports-archive.adm.cs.cmu.edu/anon/1992/CMU-CS-92-187.ps (1992)
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Speech Recognition Using Dynamical Model of Speech Production
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In: ftp://reports.adm.cs.cmu.edu/usr/anon/1992/CMU-CS-92-187.ps (1992)
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